By Bjarne S. Jensen
Dynamic Extensions of the Solow Growth Model (1956) : Editorial
German Economic Review (2009), Vol. 10 (4) : 378 - 383.
The state of affairs for growth models and economic dynamics was changed with the breakthrough by Solow (1956) : A Contribution to Theory of Economic Growth. The crucial innovation was the introduction of smooth production functions (linking factor inputs and output) that together with various saving functions provided the differential equations of capital accumulation. The economic and dynamic complexities in solving the original Solow growth model, various augmented (several factors or exhaustible natural resources) Solow growth models and optimal growth models with intertemporal saving functions are demonstrated in this special GER issue.
A stochastic growth model, with aggregate productivity shocks as the source of uncertainty, in an endogenous growth model with human capital externalities is analyzed. Labor income risk are shown to increae optimal savings and growth due to induced precautionary savings. Stochastic dynamics serve here as a powerful framework, enabling the economic analysis of realistic and complicated hypotheses.
By Oliver Budzinski
Merger Simulation in Competition Policy, forthcoming in: Journal of Competition Law & Economics
Oliver Budzinski, together with Isabel Ruhmer from Mannheim University (Germany), analysed the application of merger simulation models as a tool to evaluate proposed mergers. Merger simulations predict the effects of a proposed merger between firms by designing a model that mirrors the affected market as close as possible. The model is calibrated with real market data and predictions of post-merger prices, quantities, quality changes, etc. are derived. Thus, merger simulations represent a powerful economic tool to evaluate the welfare effects from a proposed merger. In doing so, they assist competition authorities in their decision to allow or block the merger proposal. Looking into the use of merger simulation models in competition policy, however, we identify several caveats that limit the current usefulness and workability of this tool.
By Lone Grønbæk Kronbak:
RANDOM PENALTIES AND RENEWABLE RESOURCES: A MECHANISM TO REACH OPTIMAL LANDINGS IN FISHERIES
As a spin off from the EU-funded project COBECOS (FP6), designed to deal with the costs and benefits of control strategies, Lone Grønbæk Kronbak, together with Frank Jensen, Copenhagen University (Denmark) wrote a technical modelling paper about how to design a mechanism to achieve optimal landings in fisheries. The paper deals with illegal landings as a moral hazard problem that arises because individual landings are unobservable. To overcome this problem a random penalty mechanism that reduces the information requirements, is designed. The mechanism is designed such that it secures budget balance in the case of a given number of licensed vessels. Provided risk aversion is sufficiently large and the fine is high enough, the random penalty mechanism will generate optimal individual landings. The budget balance combined with risk aversion drives the result for this advanced tax/subsidy system that does not exhaust the resource rents.
Jensen, F. & L.G. Kronbak. 2009. Random Penalties and Renewable Resources – A Mechanism to Reach Optimal Landings in Fisheries. Natural Resource Modeling. vol. 22, issue 3, pp. 393-414.